Application of TOC embedded ILP for increasing throughput of production lines

Under fairly special circumstances, there are some special methods that can be used to attempt to increase the production rate of some production line systems. In this paper an attempt has been made to use the theory of constraint (TOC) approach to identify the critical machines. Various design alternatives are considered to increase throughput of the critical machine. This process is continued till the required throughput is achieved for the entire system. For large production line systems this approach will be tedious and time consuming. Hence we have attempted to generalize the TOC approach by integer linear programming (ILP) to increase the throughput. Data has been collected from an automobile ancillary manufacturing industry to validate the model. The TOC embedded ILP has been used to increase the throughput with minimum investment.     

An empirical model for the viscosity buildup of hydroxy terminated polybutadiene based solid propellant slurry

The Polar Satellite Launch Vehicle (PSLV) makes use of hydroxy terminated polybutadiene (HTPB) based solid propellant in the booster stages, strap-ons, and the third stage. An empirical model that describes the change in viscosity of various formulations of propellant slurry with time and temperature has been developed as an extension of the Andrade equation. The model incorporates constants that account for the viscosity of the slurry caused by the combined effect of the continuous binder phase, dispersed particulate solids, and progress of crosslinking between reactive species of the binder and curators. The correspondence between predicted viscosity buildup and measured values obtained during casting of motors is verified and found satisfactory. A method of tailoring some constants, so as to make them batch-specific, is explained. Several practical applications are described. The model serves as a predictive tool for evaluating the potlife and rheological behavior of the slurry during production of large solid motors. The experimental method and approach used for data analysis can be used for other slurries that are similar in composition to propellant slurry.     

External Quantum Efficiency Exceeding 24% with CIEy Value of 0.08 using a Novel Carbene-Based Iridium Complex in Deep-Blue Phosphorescent Organic Light-Emitting Diodes

Deep-blue triplet emitters remain far inferior to standard red and green triplet emitters in terms of exhibiting high-color-purity Commission International de l'Éclairage (CIE) y values of ≤0.1, external quantum efficiencies (EQEs), and high electroluminescent brightnesses in phosphorescent organic light-emitting diodes. In fact, no deep-blue triplet emitter with color purity and high device performance has previously been reported. In this study, a deep-blue triplet emitter, mer-tris(N-phenyl, N-benzyl-pyridoimidazol-2-yl)iridium(III) (mer-Ir1) is developed, which meets the requirements of the National Television System Committee (NTSC) CIE(x, y) coordinates of (0.149, 0.085) with an extremely high EQE of 24.8% and maximum brightness (L_max) of 6453 cd m⁻², by a device with a 40 vol% doping ratio. Moreover, another device demonstrates an EQE_max of 21.3%, an L_max of 5247 cd m⁻², and CIE(x, y) coordinates of (0.151, 0.086) at a 30 vol% doping ratio. This is the first report of a high-performance, deep-blue phosphor, carbene-based Ir(III) complex device with outstanding CIE(x, y) color coordinates and a high EQE. The results of this study indicate that the novel dopant mer-Ir1 is a promising candidate for reducing power consumption in display applications.     

On the problem of spurious patterns in neural associative memorymodels

The problem of spurious patterns in neural associative memory models is discussed. Some suggestions to solve this problem from the literature are reviewed and their inadequacies are pointed out. A solution based on the notion of neural self-interaction with a suitably chosen magnitude is presented for the Hebbian learning rule. For an optimal learning rule based on linear programming, asymmetric dilution of synaptic connections is presented as another solution to the problem of spurious patterns. With varying percentages of asymmetric dilution it is demonstrated numerically that this optimal learning rule leads to near total suppression of spurious patterns. For practical usage of neural associative memory networks a combination of the two solutions with the optimal learning rule is recommended to be the best proposition.     

Dynamic mechanical properties of thermoplastic elastomers from polypropylene–natural rubber blend

The dynamic mechanical properties of thermoplastic elastomers from polypropylene natural rubber blends have been evaluated with special reference to the effect of blend ratio and extent of dynamic crosslinking of the elastomer phase. The effects of HAF black and silica fillers have also been studied. It has been found that increasing the proportion of elastomer phase reduced the storage modulus and increased the loss tangent values of the blends. The effect of dynamic crosslinking was found to be more prominent in blends containing higher proportion of elastomer phase. The improvement in storage modulus and decrease in loss tangent values were quite remarkable with increase in extent of crosslinking in these blends. The 70:30 NR:PP blend was found to exist as a two-phase system, both the components forming continuous phases of the blend.